scholarly journals Qualitative Open Science – Pain Points and Perspectives

2021 ◽  
Author(s):  
Sarahanne Miranda Field ◽  
Don van Ravenzwaaij ◽  
Merle-Marie Pittelkow ◽  
Joyce M. Hoek ◽  
Maarten Derksen
Keyword(s):  
Qualitative Research ◽  
Data Quality ◽  
Data Sharing ◽  
Qualitative Data ◽  
Scientific Research ◽  
Cost Benefit ◽  
Open Science ◽  
Research Practice ◽  
Qualitative Researcher ◽  
The Cost

Adopting some practical elements of open science – a movement whose goal is to make scientific research available for everyone – presents unique chal- lenges for qualitative researchers, particularly when it comes to data sharing. In this article, we discuss the issue of open qualitative data, arguing that while concerns about ethics and loss of data quality are legitimate, they do not pose so great a problem as to preclude qualitative researchers from ef- fectively practicing open science. We describe the cost-benefit balance that each qualitative researcher takes into account as they choose whether or not to share their data, and highlight the fact that qualitative research practice lends itself to transparency and integrity by its reliance on reflexivity, and other practices such as member checking and using multiple coders. We con- clude with a reminder to readers that fruitful open science does not require for one to engage in all possible practices for a given study; only those which are appropriate and feasible.

scholarly journals Are we ready to share qualitative research data? Knowledge and preparedness among qualitative researchers, IRB members, and data repository curators

2020 ◽  
Vol 43 (4) ◽  
pp. 1-23 ◽  
Author(s):  
Jessica Mozersky ◽  
Heidi Walsh ◽  
Meredith Parsons ◽  
Tristan McIntosh ◽  
Kari Baldwin ◽  
...  
Keyword(s):  
Data Sharing ◽  
Qualitative Data ◽  
The United States ◽  
Open Science ◽  
Data Repository ◽  
Data Sets ◽  
Ethical Challenges ◽  
Staff Members ◽  
Stakeholder Groups ◽  
Secondary Analyses

Data sharing maximizes the value of data, which is time and resource intensive to collect. Major funding bodies in the United States (US), like the National Institutes of Health (NIH), require data sharing and researchers frequently share de-identified quantitative data. In contrast, qualitative data are rarely shared in the US but the increasing trend towards data sharing and open science suggest this may be required in future. Qualitative methods are often used to explore sensitive health topics raising unique ethical challenges regarding protecting confidentiality while maintaining enough contextual detail for secondary analyses. Here, we report findings from semi-structured in-depth interviews with 30 data repository curators, 30 qualitative researchers, and 30 IRB staff members to explore their experience and knowledge of QDS. Our findings indicate that all stakeholder groups lack preparedness for QDS. Researchers are the least knowledgeable and are often unfamiliar with the concept of sharing qualitative data in a repository. Curators are highly supportive of QDS, but not all have experienced curating qualitative data sets and indicated they would like guidance and standards specific to QDS. IRB members lack familiarity with QDS although they support it as long as proper legal and regulatory procedures are followed. IRB members and data curators are not prepared to advise researchers on legal and regulatory matters, potentially leaving researchers who have the least knowledge with no guidance. Ethical and productive QDS will require overcoming barriers, creating standards, and changing long held practices among all stakeholder groups.

scholarly journals Qualitative Researcher Reflexivity: A Follow-Up Study with Female Sexual Assault Survivors

2015 ◽  
Author(s):  
Stephanie Hoover ◽  
Susan Morrow
Keyword(s):  
Qualitative Research ◽  
Sexual Assault ◽  
Qualitative Data ◽  
Ethical Issues ◽  
Research Process ◽  
Multiple Sources ◽  
Qualitative Researcher ◽  
Sexual Assault Survivors ◽  
Follow Up Study

Motivated by researcher reflexivity, the author sought to learn from participants about the sensitive, ethical issues of the qualitative research process. The current study followed up with eight women who had previously participated in an interview-based study about sexual assault disclosure. Multiple sources of qualitative data were triangulated, including interviews, follow-up interviews, interviews from the original study, and participant checks. Phenomenological analysis yielded five themes: (a) Meaning of Participation, (b) Trust in the Researcher, (c) Connection with the Other Participants, (d) Changing Comfort, and (e) Recommendations to Increase Participants’ Comfort. Based on these results, recommendations are provided for researchers conducting reflexive qualitative research practices.

Challenges of translating qualitative management data

2018 ◽  
Vol 33 (1) ◽  
pp. 66-79 ◽  
Author(s):  
Jouharah M. Abalkhail
Keyword(s):  
Qualitative Research ◽  
Qualitative Data ◽  
Deep Understanding ◽  
Validity And Reliability ◽  
Qualitative Researcher ◽  
Content Type ◽  
Language And Culture ◽  
Depth Of Knowledge ◽  
Language Data ◽  
Combination Of Methods

Purpose The purpose of this paper is to discuss the challenges of translating qualitative data from Arabic to English within the field of gender and management studies. Design/methodology/approach This paper presents a real experience of translating qualitative data from Arabic to English within the management area in Saudi Arabia. Data were collected from interviewing female managers working in the Saudi public sector. Findings Translating qualitative data from Arabic to English is not a straightforward process. During the translation of this cross-cultural qualitative research, three challenges were faced: the embeddedness of the language meaning in the culture, positionality and its influence on data production and language differences. The study found that, in absence of a standard way for translating cross-linguistic qualitative research, a combination of methods is found to be useful to increase the validity and reliability of the study findings. Researchers who conduct qualitative insider research and who translate their own data are in a better position to do cross-language data analysis. Originality/value This paper contributes to the literature by showing that translating Arabic texts regarding gender, management and leadership is embedded within historical, cultural, political and institutional contexts, requiring a deep understanding of both language and culture to produce a depth of knowledge. Also, the novelty of this study is that it highlights the importance of being an insider qualitative researcher and translating the research data, as researcher offers significant opportunities for close attention to certain points in the text; and this could add value to the analysis as a way to establish validity of interpretations.

scholarly journals How I became a qualitative researcher?

2012 ◽  
Vol 30 (1) ◽  
pp. 258-275
Author(s):  
Florentina Scârneci
Keyword(s):  
Qualitative Research ◽  
Personal Experience ◽  
Quantitative Research ◽  
Scientific Research ◽  
Sociological Research ◽  
Qualitative Researcher ◽  
The Social ◽  
Social Scientific ◽  
Theoretical Saturation ◽  
Special Case

Abstract: The present article presents the personal experience of the author with research methodologies.Some limits of the social scientific research are being analyzed, regarding two of the stages of research:theoretical framework and operationalization; this is the way in which the validity of the criteria and theconstruct validity came into discussion. At the same time, the character of sociological theories and theirutility in scientific research are under discussion. Reasons for which qualitative is chosen are listed despitethe constant disapproval of this method in Romanian sociology (and it’s marginalization in Central – EastEurope). The advantages of qualitative research in socio-human sciences are presented (what is being researched,through what methods, with what results). The special case of using the focus-group at a large scaleis being analyzed (its use without following two of the major qualitative principals: theoretical samplingand theoretical saturation). The article advocates for the usage of qualitative and it is written in a personaland provocative style.Key words: sociological research methodology, qualitative research, quantitative research, validity. SANTRAUKAKODĖL AŠ PASIRINKAU KOKYBINIO TYRIMO BŪDĄ?Straipsnis parengtas remiantis asmenišku autorės, dirbančios tyrimo metodologijų srityje, patyrimu.Analizuojami sociologinio mokslinio tyrimo trūkumai, susiję su dviem tyrimo pakopomis: teorine struktūrair operacionalizacija. Viena vertus, svarbu kriterijų ir konstrukcijų pagrįstumas, kita vertus, sociologiniųteorijų taikymo moksliniams tyrimams patikimumas. Aptariamos kokybinio metodo pasirinkimo priežastysir aplinkybės, rodančios, kad šis metodas Rumunijoje ir Centrinėje Rytų Europoje yra marginalizuojamas.Svarstomi įvairūs kokybinio metodo privalumai, įskaitant plačios apimties focus-grupių pavyzdžius. Straipsnioautorė nevengia kokybinio tyrimo būdo apologijos provokacinio stiliaus.

scholarly journals The second step in data analysis: Coding qualitative research data

2015 ◽  
Vol 03 (01) ◽  
pp. 007-010 ◽  
Author(s):  
Heather Stuckey
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Qualitative Data ◽  
Research Question ◽  
A Priori ◽  
Research Data ◽  
Second Step ◽  
Diabetes Research ◽  
Data Dictionary ◽  
Qualitative Researcher

AbstractCoding is a process used in the analysis of qualitative research, which takes time and creativity. Three steps will help facilitate this process:1. Reading through the data and creating a storyline;2. Categorizing the data into codes; and3. Using memos for clarification and interpretation.Remembering the research question or storyline, while coding will help keep the qualitative researcher focused on relevant codes. A data dictionary can be used to define the meaning of the codes and keep the process transparent. Coding is done using either predetermined (a priori) or emergent codes, and most often, a combination of the two. By using memos to help clarify how the researcher is constructing the codes and his/her interpretations, the analysis will be easier to write in the end and have more consistency. This paper describes the process of coding and writing memos in the analysis of qualitative data related to diabetes research.

scholarly journals Understanding and Evaluating Qualitative Research

2002 ◽  
Vol 36 (6) ◽  
pp. 717-732 ◽  
Author(s):  
Ellie Fossey ◽  
Carol Harvey ◽  
Fiona Mcdermott ◽  
Larry Davidson
Keyword(s):  
Qualitative Research ◽  
Qualitative Data ◽  
Good Practice ◽  
Mental Health Research ◽  
Social Contexts ◽  
Social Worlds ◽  
Critical Research ◽  
Qualitative Researcher ◽  
Research Paradigms ◽  
Subjective Meanings

Qualitative research aims to address questions concerned with developing an understanding of the meaning and experience dimensions of humans’ lives and social worlds. Central to good qualitative research is whether the research participants’ subjective meanings, actions and social contexts, as understood by them, are illuminated. This paper aims to provide beginning researchers, and those unfamiliar with qualitative research, with an orientation to the principles that inform the evaluation of the design, conduct, findings and interpretation of qualitative research. It orients the reader to two philosophical perspectives, the interpretive and critical research paradigms, which underpin both the qualitative research methodologies most often used in mental health research, and how qualitative research is evaluated. Criteria for evaluating quality are interconnected with standards for ethics in qualitative research. They include principles for good practice in the conduct of qualitative research, and for trustworthiness in the interpretation of qualitative data. The paper reviews these criteria, and discusses how they may be used to evaluate qualitative research presented in research reports. These principles also offer some guidance about the conduct of sound qualitative research for the beginner qualitative researcher.

scholarly journals Data Analysis Methods for Qualitative Research: Managing the Challenges of Coding, Interrater Reliability, and Thematic Analysis

2018 ◽  
Author(s):  
Michael Belotto
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Thematic Analysis ◽  
Interrater Reliability ◽  
Qualitative Data ◽  
Sources Of Information ◽  
Qualitative Data Analysis ◽  
Qualitative Researcher ◽  
First Time ◽  
Data Analysis Methods

The purpose of this article is to provide an overview of some of the principles of data analysis used in qualitative research such as coding, interrater reliability, and thematic analysis. I focused on the challenges that I experienced as a first-time qualitative researcher during the course of my dissertation, in the hope that how I addressed those difficulties will better prepare other investigators planning endeavors into this area of research. One of the first challenges I encountered was the dearth of information regarding the details of qualitative data analysis. While my text books explained the general philosophies of the interpretive tradition and its theoretical groundings, I found few published studies where authors actually explained the details pertaining to exactly how they arrived at their findings. Some authors even confirmed my own experience that few published studies described processes such as coding and methods to evaluate interrater reliability. Herein, I share the sources of information that I did find and the methods that I used to address these challenges. I also discuss issues of trustworthiness and how matters of objectivity and reliability can be addressed within the naturalistic paradigm.

scholarly journals Attitudes towards Open Science and Public Data Sharing: A Survey among Members of the German Psychological Society.

2019 ◽  
Author(s):  
Andrea Abele-Brehm ◽  
Mario Gollwitzer ◽  
Ulf Steinberg ◽  
Felix D. Schönbrodt
Keyword(s):  
Data Sharing ◽  
Structural Changes ◽  
Research Output ◽  
Open Data ◽  
Cost Benefit ◽  
Open Science ◽  
Early Career ◽  
Positive Attitudes ◽  
Public Data ◽  
Materials Used

Central values of science are, among others, transparency, verifiability, replicability and openness. The currently very prominent Open Science (OS) movement supports these values. Among its most important principles are open methodology (comprehensive and useful documentation of methods and materials used), open access to published research output, and open data (making collected data available for re-analyses). We here present a survey conducted among members of the German Psychological Society (N = 337), in which we applied a mixed-methods approach (quantitative and qualitative data) to assess attitudes towards OS in general and towards data sharing more specifically. Attitudes towards OS were distinguished into positive expectations (“hopes”) and negative expectations (“fears”). These were un-correlated. There were generally more hopes associated with OS and data sharing than fears. Both hopes and fears were highest among early career researchers and lowest among professors. The analysis of the open answers revealed that generally positive attitudes towards data sharing (especially sharing of data related to a published article) are somewhat diminished by cost/benefit considerations. The results are discussed with respect to individual researchers’ behavior and with respect to structural changes in the research system.

scholarly journals Good listening: A key element in establishing quality in qualitative research

2021 ◽  
pp. 146879412110394
Author(s):  
Einat Lavee ◽  
Guy Itzchakov
Keyword(s):  
Qualitative Research ◽  
Organizational Behavior ◽  
Qualitative Data ◽  
Data Gathering ◽  
Blind Spot ◽  
Research Quality ◽  
Qualitative Researcher ◽  
Interview Guide ◽  
Listening Studies

What is “good” qualitative research? Considerable literature articulates criteria for quality in qualitative research. Common to all these criteria is the understanding that the data gathering process, often interviews, is central in assessing research quality. Studies have highlighted the preparation of the interview guide, appropriate ways to ask questions, and especially the interaction between interviewer and interviewee. To a lesser extent, qualitative scholars mention the importance of the interviewer’s listening abilities in obtaining the interviewee’s cooperation. Based on results of listening studies in the fields of psychology and organizational behavior, we argue that good listening is crucial for assessing the quality of qualitative research, yet remains a blind spot in qualitative data gathering. Drawing on our experience as qualitative researcher and listening researcher, we present practices for enhancing good listening in qualitative research, thereby enabling researchers to calibrate themselves as research instruments and obtain richer data.

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